Gender Identity and Expression
Week 8
1
Objectives
1. Describe research methods for studying gender
identity and expression as they relate to health
2. Identify some key health disparities in relation to
gender identity and expression
3. Learn more details about the case-control study
design and apply to a health problem
2
Case-control
3
Process
1. Participants selected on the basis of if they do
(cases) or do not (controls) have a particular
disease/outcome
2. Then compare proportion having an exposure
Approach began relatively recently in response to
shift from acute to chronic public health
4
Strengths
•
Avoids logistic difficulties of studying diseases of long latent periods
•
Efficient design
•
With respect to time, money (disease already occurred), and long latent
periods
•
Can get adequate numbers of diseased and non-diseased people, ideal
when outcome is rare
•
Ideal for evaluating multiple exposures for one outcome, as well as
interrelationships of various exposures
•
Can test hypotheses or explore a wide range of exposures (“fishing
expedition”) for future studies
•
Useful in early stages of knowledge
5
Limitations
•
Bias susceptibility
•
Selection bias (differential selection of cases or controls on basis of
exposure status)
•
Observation bias (differential recording of exposure between study
groups based on disease status)
•
Challenge to determine temporality
•
Difficulty in knowing appropriate time window for exposure and getting
accurate past exposure information
•
Cannot calculate incidence rates/risk, nor relative or attributable rates/risk
directly, must estimate with odds ratio (OR)
•
Great first study but must design carefully
6
Source of Cases
Need definition of disease (preferably homogenous for similar mechanisms), strict diagnostic criteria
Must be selected independently of exposure
Potential sources
Hospital-based (easy and inexpensive)
•
•
Advantages
•
Convenient, easily identified, sufficient numbers, inexpensive, minimal effort
•
Cases/controls similar in accuracy of recall (both “sick”), minimizes recall bias
•
Good cooperation, minimizing non-response bias
Disadvantages
•
Controls are ill, may not represent exposure distribution in population from which cases derived
•
Disease for which controls hospitalized may be associated with study exposure
•
•
e.g., smoking and lung – wouldn’t use bronchitis, COPD
Selection factors for hospitalization may differ between cases and controls (referral patterns, primary vs. tertiary
hospitals)
7
Sources of Cases cont.
Population-based (avoids potential bias but logistic and cost considerations)
•
Advantages
•
•
Generally ensures comparability –from same source population
Disadvantages
•
Difficult to enumerate all members of population to select from (town lists in MA)
•
Difficult to gain cooperation for participation – time, motivation.
•
Non-response greater than hospitalized cases – major threat to validity
•
Expensive and time consuming
•
Quality of information – may not recall exposures as accurately as cases
Others: disease registries; special surveys; random digit dialing; friends, spouses, sibs,
neighbor controls
8
Sources of Controls
Ideally, direct random sample of the reference
population from which the cases originated
Controls must be sampled independently of exposure
9
Bias
Chance, bias, and confounding issue in any analytic study
Types of bias not unique to case-control, but more of a possibility because of
design
•
Selection bias
•
•
Recall bias
•
•
Occurs when controls or cases are more (or less) likely to be included if
they have been exposed (inclusion in study is not independent of exposure)
Relates to differences in the ways exposure information is remembered/
reported by cases, who have experienced an adverse health outcome, and
by controls, who have not
Can result in an overestimate or underestimate
10
Bias cont.
Careful of interpretation of data-derived hypotheses (chance)
Most case-control studies test a small number of specific hypotheses
Often collect data on many risk factors and conduct numerous comparisons
Must distinguish between
•
Tests of hypotheses specified in advance (a priori hypotheses)
•
“Fishing expeditions:” associations emerge as data analyzed (a
posteriori hypotheses)
•
Interpret with caution
•
Can then be tested in studies specifically designed to do so
11
How to Design a Study
Cell Phones and Brain Cancer
12
“…The final, definitive trials on phone radiation may not settle
this issue—but, as of now, the evidence remains far from
convincing. Understanding the rigor, labor, evidence and time
required to identify a real carcinogen is the first step to
understanding what does and does not cause cancer.”
Mukherjee, Siddhartha. "Do Cellphones Cause Brain Cancer?" New York Times Magazine, April 13, 2011.
© The New York Times. All rights reserved. This content is excluded from our Creative Commons license.
For more information, see http://ocw.mit.edu/help/faq-fair-use/.
13
Brain Cancer
•
Gliomas—tumor of the brain, arising from glial cells
•
77% of primary malignant brain tumors
•
Rare ~9 cases per 100,000 person-years
•
Median age at diagnosis varies (range: 43-64)
•
Causes are mostly unknown
•
•
High doses of ionizing radiation and rare genetic factors
Very poor prognosis
•
Survival related to age at diagnosis (better survival in young) and
histologic tumor sub-type
14
Lag (or Latent) Period
Induction period for high dose
ionizing radiation: ~10 years
15
Design your
own study
How would you design a
study to answer this
question?
• Case-control
• Cohort
• Trial/intervention
Image courtesy of Sheila Sund on flickr. License CC BY-NC.
16
Questions to Consider
•
What is the gap in knowledge you hope to address?
•
What study design do you propose to use?
•
What will be the specific aims (hypotheses)?
•
Exposure and outcome: how will they be defined?
•
Target population?
•
What other variables will you collect as possible confounding variables or effect modifiers?
•
Analytical approach
•
How will you ensure that chance, bias, and confounding will be minimized as alternative
explanations for your findings?
•
What do you anticipate will be the strengths and weaknesses of your study?
•
What will be the likely next steps?
17
Case-Control
Cohort
Trial
Strengths
+ Efficient use of time/money
+ Efficient for long latent
period (ideal for rare
outcomes)
+ Can evaluate multiple
exposures
+ Can evaluate multiples
outcomes
+ Efficient for rare exposures
+ Correct temporal sequence
+ Good exposure information
+ If prospective, can
minimize bias in exposure
ascertainment
+ Can directly measure
incidence
+ "Gold standard�
+ Optimal for small to
moderate-sized effects
+ Greater degree of control
over exposure
+ Randomization:
minimizes selection bias
and confounding
+ Placebo: minimizes
observation bias
Limitations
-Temporal sequence is hard
to establish
- Inefficient for rare
exposures
-Cannot calculate incidence
rates
Potential biases:
-Selection bias
-Observation bias
-Recall bias
-Rare diseases: require
large sample size (inefficient)
-Latent period: requires long
follow-up (if prospective)
-Need to minimize loss to
follow-up for validity
-If retrospective, requires
availability of pre-recorded
information on exposure and
confounding variables
- Logistically more difficult
and expensive
-Ethical issues
-Compliance and losses to
follow-up
18
Some questions never go away…
“Sheryl Crow: My Brain Tumor May Be Related to Cell Phone Use”
“There are no doctors that will confirm that but I do have the theory that it’s possible
that it’s related to that. I used to spend hours on the old archaic cell phones.”
Triggs, Charlotte, and Marla Lehner. “Sheryl Crow: My Brain Tumor May Be Related to Cell Phone Use.”
People, 2012. © Time, Inc. All rights reserved. This content is excluded from our Creative Commons
license. For more information, see http://ocw.mit.edu/help/faq-fair-use/.
19
© Brittany M. Charlton 2016
20
MIT OpenCourseWare
http://ocw.mit.edu
WGS.151 Gender, Health, and Society
Spring 2016
For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.